6.1.2  Plant biomass

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Apart from some specialised applications in leaf expansion, organ enlargement or in vitro culture of cell suspensions, cell number is an impractical measure of growth in whole plants. Instead, fresh or oven-dried biomass (W) is generally taken as a surrogate for carbon gain and referenced to the number of days elapsed between successive observations. At any instant, relative growth rate, RGR (d–1), can be expressed in terms of differential calculus as RGR = (1/W)(dW/dt) (compare Equation 6.2.) so that RGR is increment in dry mass (dW) per increment in time (dt) divided by existing biomass (W). Averaged over a time interval t1 to t2 during which time biomass increases from W1 to W2, RGR (d–1) can be calculated from


Net gain in biomass (W) is clearly an outcome of CO2 assimilation by leaves minus respiratory loss by the entire plant. Leaf area can therefore be viewed as a driving variable, and biomass increment (dW) per unit time (dt) can then be divided by leaf area (A) to yield the net assimilation rate, NAR (g m–2 d–1), where



Averaged over a short time interval (t1 to t2 days) and provided whole-plant biomass and leaf area are linearly related (see Radford 1967 and literature cited),



NAR thus represents a plant’s net photosynthetic effectiveness in capturing light, assimilating CO2 and storing photoassimilate. Variation in NAR can derive from differences in canopy architecture and light interception, photosynthetic activity of leaves, respiration, transport of photoassimilate and storage capacity of sinks, or even the chemical nature of stored products.

Since leaf area is a driving variable for whole-plant growth, the proportion of plant biomass invested in leaf area or ‘leafiness’ will have an important bearing on RGR, and can be conveniently defined as leaf area ratio, LAR (m2 g–1), where



At any instant, or in practice at any harvest, LAR can be taken as A/W and can be factored into two components, namely specific leaf area (SLA) and leaf weight ratio (LWR). SLA is simply a ‘ratio’ of leaf area (A) to leaf mass (WL) (dimensions m2 g–1) and LWR is a true ratio of leaf mass (WL) to total plant mass (W) (dimensionless). Thus,




Alternatively, and as commonly employed for growth analysis, average LAR over the growth interval t1 to t2 is simply



Expressed this way, LAR becomes a more meaningful growth index than A/W (Equation 6.8) and can help resolve sources of variation in RGR. If both A and W are increasing exponentially so that W is proportional to A, it follows that



or, summarised in terms of now familiar growth indices,



or more explicitly,


In practice, such ideal conditions are only rarely met, and these multiplier-product relationships must be applied with caution (see especially Williams 1946 and Radford 1967). Nevertheless, where valid application is possible, sources of variation in RGR can be partitioned between NAR, LWR and SLA, or simply between NAR and LAR. Such outcomes provide particularly useful insights on driving variables in process physiology and ecology.

Basic concepts of classic plant growth analysis as described above apply to individuals, and ideally those growth indices would be derived from non-destructive assay. Experimentally, a population of fast-growing (small) plants is sampled at frequent intervals, and sample means are then taken as representative of the population. Relatively few harvests (commonly weekly) but relatively large numbers of replicates (commonly six to eight plants) are employed. Harvested plants are subdivided into component parts while still fresh, leaf area is measured, and all biomass subsequently oven dried for dry mass deter-mination. An error estimate for RGR can be calculated by pairing plants across harvests, that is, taking the largest plant at t1 and the largest at t2 and calculating RGR, then the next-largest pair and so on. Mean RGR and variance are then derived (see Poorter (1989) for more discussion on pairing, and Poorter and Lewis (1996) for more on sampling methods).

Functional growth analysis

Classic plant growth analysis continues to find application in resolving sources of variation in RGR but suffers from statistical deficiencies and strict prerequisities for valid application of the formulae discussed above. Functional growth analysis was developed during the 1960s to overcome these limitations and was made feasible with the advent of computer-based data analysis at about that time. In this technique (see Hunt 1982) curves generated by mathematical functions are fitted to both A and W (either original values or ln-transformed data). RGR at any particular point in time is then calculated as the slope of ln W versus time. Other indices can be calculated once an adequate relationship between ln A and time is established. In effect, an adequate relationship between ln W and ln A versus time allows calculation of instantaneous values for RGR, NAR and LAR. As mentioned above, the slope of ln W versus time yields RGR, and at that same instant A can be derived from the ln A versus time relationship, allowing LAR (A/W) to be calculated. With RGR already derived, NAR is then RGR/LAR.

Functional growth analysis enables experimenters to follow a time-course in growth indices and to derive instantaneous values. In practical terms, large harvests at weekly intervals are no longer needed. Instead, smaller harvests of two to four plants every 3–4 d are sufficient. However, data analysis remains critical, and especially important is choice of a mathematical function with biologically meaningful parameters that best fits ln-transformed values (see Hunt 1978, 1982 for further details).

Growth indices in summary

Whole-plant growth is amenable to analysis via either classic or functional methods. In either case, five key indices are commonly derived as an aid to understanding growth responses. Mathematical and functional definitions of those terms are summarised below.


LAR and SLA both carry dimensions of cm2 g–1 (or m2 kg–1) and are therefore not true ratios as implied by the term ‘ratio’. LWR is a true dimensionless ratio. The reciprocal of SLA, or leaf mass per unit leaf area, is often but mistakenly referred to as specific leaf weight (SLW). By definition, any ‘specific’ index must be referenced to mass, so that SLW will always equal 1 (Jarvis 1985). For that reason, and where such data warrant inclusion, leaf mass to leaf area ‘ratio’ will be used rather than SLW.